Altered resting-state functional connectivity of striatal-thalamic circuit in bipolar disorder.

Bipolar disorder is characterized by internally affective fluctuations. The abnormality of inherently mental state can be assessed using resting-state fMRI data without producing task-induced biases. In this study, we hypothesized that the resting-state connectivity related to the frontal, striatal, and thalamic regions, which were associated with mood regulations and cognitive functions, can be altered for bipolar disorder. We used the Pearson's correlation coefficients to estimate functional connectivity followed by the hierarchical modular analysis to categorize the resting-state functional regions of interest (ROIs). The selected functional connectivities associated with the striatal-thalamic circuit and default mode network (DMN) were compared between bipolar patients and healthy controls. Significantly decreased connectivity in the striatal-thalamic circuit and between the striatal regions and the middle and posterior cingulate cortex was observed in the bipolar patients. We also observed that the bipolar patients exhibited significantly increased connectivity between the thalamic regions and the parahippocampus. No significant changes of connectivity related to the frontal regions in the DMN were observed. The changed resting-state connectivity related to the striatal-thalamic circuit might be an inherent basis for the altered emotional and cognitive processing in the bipolar patients.

Classification of bipolar disorder using basal-ganglia-related functional connectivity in the resting state.

The emotional and cognitive symptoms of bipolar disorder (BD) are suggested to involve in a distributed neural network. The resting-state functional magnetic resonance imaging (fMRI) offers an important tool to investigate the alterations in brain network level of BD. The aim of this study was to discriminate BD patients from healthy controls using whole-brain resting-state functional connectivity patterns. The majority of most discriminating functional connectivities were between the basal ganglia and three core neurocognitive networks, including the default mode, executive control and salience networks. Using these resting-state functional connectivities between the basal ganglia and three core neurocognitive networks as the features, the clustering accuracy achieved 90%.

Cortical shape and curvedness analysis of structural deficits in remitting and non-remitting depression.

In morphometric neuroimaging studies, the relationship between brain structural changes and the antidepressant treatment response in patients with major depressive disorder has been explored to search depression-trait biomarkers. Although patients were treated with serotonin-related drugs, whether the same treatment resulted in remission and non-remission in depressed patients is currently under investigation. We recruited 25 depressed patients and 25 healthy controls and acquired volumetric magnetic resonance imaging of each participant. We used the shape index and curvedness to classify cortical shapes and quantify shape complexities, respectively, in studying the pharmacological effect on brain morphology. The results showed that different regions of structural abnormalities emerged between remitting and non-remitting patients when contrasted with healthy controls. In addition to comparing structural metrics in each cortical parcellation, similar to the traditional voxel-based morphometric method, we highlighted the importance of structural integrity along the serotonin pathway in response to medication treatment. We discovered that disrupted serotonin-related cortical regions might cause non-remission to antidepressant treatment from a pharmacological perspective. The anomalous areas manifested in non-remitting patients were mainly in the frontolimbic areas, which can be used to differentiate remitting from non-remitting participants before medication treatment. Because non-remission is the failure to respond to treatment with serotonin-related drugs, our method may help clinicians choose appropriate medications for non-remitting patients.

Shape and curvedness analysis of brain morphology using human fetal magnetic resonance images in utero.

The 3-D morphological change has gained increasing significance in recent investigations on human fetal brains. This study uses a pair of new indices, the shape index (SI) and curvedness index (CVD), to quantify 3-D morphological changes in developing brains from 22 to 33 weeks of gestation. The SI was used to automatically locate the gyral nodes and sulcal pits, and the CVD was used to measure the degree of deviation of cortical shapes from a flat plane. The CVD values of classified regions were compared with two traditional biomarkers: cerebral volume and cortical surface area. Because the fetal brains dramatically deform with age, the age effect was controlled during the comparison between morphological changes and volume and surface area. The results show that cerebral volume, the cortical surface area, and the CVD values of gyral nodes and sulcal pits increased with gestational age. However, with age controlled, the CVD values of gyral nodes and sulcal pits did not correlate with cerebral volume, but the CVD of gyral nodes increased slightly with the cortical surface area. These findings suggest that the SI, in conjunction with the CVD, provides developmental information distinct from the brain volumetry. This approach provides additional insight into 3-D cortical morphology in the assessment of fetal brain development.

Regional quantification of developing human cortical shape with a three-dimensional surface-based magnetic resonance imaging analysis in utero.

Although regional differences in cerebral volume have been revealed in developing human brains, little is known regarding the regionalization of cortical shape. This study documented the regional and quantitative shape difference of cortical surfaces for in utero normal fetal brains over a time period essential for the formation of primary cortical folding (22-33 weeks). Each brain surface with complete three-dimensional morphology was manually extracted from the reconstructed image, which combined surface information from three orthogonal magnetic resonance images in utero. An innovative parcellation was used to dissect the fetal brains into frontal, parietal, temporal and occipital lobes, and to avoid the determination of non-existent and immature sulci for young fetuses. Distinct cortical shapes were encoded by the shape index automatically. The results of this study show faster shape changes in the occipital lobe than in other regions. Both regional and global shape patterns show that the gyral surface smoothens, whereas the sulcal surface becomes more angular, with gestational age. In addition, the smoothing of gyri is related mainly to the changes in shape of gyral crowns. This study presents the regional differences in early gyrification from the novel aspect of shape. The results of shape pattern analysis for normal fetuses may act as a reference in assessments of prenatal brain pathology and in extensive comparisons between various life stages.

Reorganization of functional connectivity during the motor task using EEG time-frequency cross mutual information analysis.

OBJECTIVE: This study investigates the functional organization of cortical networks during self-determinant arm movement using the time sequences of the alpha (8-12 Hz) and beta (16-25 Hz) bands. METHODS: The time-frequency cross mutual information (TFCMI) method was used to estimate the EEG functional connectivity in the alpha and beta bands for seven healthy subjects during four functional states: the resting, preparing, movement-onset, and movement-offset states. RESULTS: In the preparing state, the maintenance of the central-executive network (CEN, prefrontal-parietal connection) suppressed the motor network in the alpha band to plan the next movement, whereas the CEN was deactivated in the beta band to retain visual attention (the frontal-occipital connection). A significant decrease of the CEN in the alpha band occurred after a visual cue in the movement-onset state, followed by a significant increase in motor-network connectivity in the beta band until the movement-offset state. CONCLUSIONS: The temporal-spectral modulation mechanism allows the brain to manifest multiple functions subject to energy budget. SIGNIFICANCE: The TFCMI method was employed to estimate EEG functional connectivity and effectively demonstrate the reorganization process between four functional states.

Morphological regionalization using fetal magnetic resonance images of normal developing brains.

Regional differences in human brain development during infancy have been studied for many years, but little is known about how regionalization of the brain proceeds during intrauterine life. We investigated the regionalization of cerebral volume and cortical convolutions based on the volumetric magnetic resonance images (MRIs) of 43 fetuses, ranging from 21 to 37 weeks of gestation. Two plausible parcellations of MRI are proposed, and curvature index together with gyrification index are used to quantify the regional cortical convolutions. Our results elucidate that the cortical foldings among different brain regions develop at comparable rates, suggesting a similar uniformity of changes in size of the cortical sheet in these regions over time. On the contrary, the growth of the cerebral volume presents regional difference, with the frontal and parieto-temporal regions growing significantly faster than other regions due to the contribution from expansion of basal ganglia. This quantitative regional information suggests that cerebral volume is not a relevant parameter to measure in relation to gyrification, and that the size of the cortical sheet is more likely to be directly related to cortical folding. The availability of quantitative regional information on normal fetal brains in utero will allow clinical application of this information when probing neurodevelopmental disorders in the future.

Early detection of periodic sharp wave complexes on EEG by independent component analysis in patients with Creutzfeldt-Jakob disease.

Sporadic Creutzfeldt-Jakob disease (sCJD) is the most common human prion disease. EEG is the method of choice to support the diagnosis of a human prion disease. Periodic sharp wave complexes (PSWCs) on the EEG usually indicate a progressive stage of CJD. However, PSWCs only become obvious at around 8 to 12 weeks after the onset of clinical symptoms, and in a few cases, even later. Independent component analysis (ICA) is a new technique to separate statistically independent components from a mixture of data. This study recruited seven patients who fit the criteria of CJD between 2002 and 2005 and 10 patients with Alzheimer's disease (AD) as control subjects. Using an ICA algorithm, we were able to split typical PSWCs into several independent temporal components in conjunction with spatial maps. The PSWCs were not observed in the initial EEG studies of patients with either AD or CJD. However, the ICA algorithm was able to extract periodic discharges and epileptiform discharges from raw EEG of patients with CJD at as early as 3 to 5 weeks after disease onset. Such discharges otherwise could hardly be discerned by visual inspection. In conclusion, ICA may increase the sensitivity of EEG and facilitate the early diagnosis of CJD.

Blind source separation of concurrent disease-related patterns from EEG in Creutzfeldt-Jakob disease for assisting early diagnosis.

Creutzfeldt-Jakob disease (CJD) is a rare, transmissible and fatal prion disorder of brain. Typical electroencephalography (EEG) patterns, such as the periodic sharp wave complexes (PSWCs), do not clearly emerge until the middle stage of CJD. To reduce transmission risks and avoid unnecessary treatments, the recognition of the hidden PSWCs forerunners from the contaminated EEG signals in the early stage is imperative. In this study, independent component analysis (ICA) was employed on the raw EEG signals recorded at the first admissions of five patients to segregate the co-occurrence of multiple disease-related features, which were difficult to be detected from the smeared EEG. Clear CJD-related waveforms, i.e., frontal intermittent rhythmical delta activity (FIRDA), fore PSWCs (triphasic waves) and periodic lateralized epileptiform discharges (PLEDs), have been successfully and simultaneously resolved from all patients. The ICA results elucidate the concurrent appearance of FIRDA and PLEDs or triphasic waves within the same EEG epoch, which has not been reported in the previous literature. Results show that ICA is an objective and effective means to extract the disease-related patterns for facilitating the early diagnosis of CJD.

Recognition of motor imagery electroencephalography using independent component analysis and machine classifiers.

Motor imagery electroencephalography (EEG), which embodies cortical potentials during mental simulation of left or right finger lifting tasks, can be used to provide neural input signals to activate a brain computer interface (BCI). The effectiveness of such an EEG-based BCI system relies on two indispensable components: distinguishable patterns of brain signals and accurate classifiers. This work aims to extract two reliable neural features, termed contralateral and ipsilateral rebound maps, by removing artifacts from motor imagery EEG based on independent component analysis (ICA), and to employ four classifiers to investigate the efficacy of rebound maps. Results demonstrate that, with the use of ICA, recognition rates for four classifiers (fisher linear discriminant (FLD), back-propagation neural network (BP-NN), radial-basis function neural network (RBF-NN), and support vector machine (SVM)) improved significantly, from 54%, 54%, 57% and 55% to 70.5%, 75.5%, 76.5% and 77.3%, respectively. In addition, the areas under the receiver operating characteristics (ROC) curve, which assess the quality of classification over a wide range of misclassification costs, also improved from .65, .60, .62, and .64 to .74, .76, .80 and .81, respectively.